Interaction Networks (IN) use graph-based deep neural networks to model object relations, enabling accurate long-term physical predictions and energy inference.

Peter W. Battaglia, Razvan Pascanu, Matthew Lai et al.

3D-EPN combines shape synthesis for high-accuracy 3D shape completion.

Angela Dai, Charles Ruizhongtai Qi, Matthias Nießner

Proposes shallow-wide residual networks outperforming ResNet-200, enhancing image classification and segmentation with improved efficiency.

Zifeng Wu, Chunhua Shen, Anton van den Hengel

NewsQA employs a four-stage data collection, with over 100,000 QA pairs emphasizing reasoning, surpassing simple word matching.

Adam Trischler, Tong Wang, Xingdi Yuan et al.

Proposes a DenseNet-based fully convolutional network for semantic segmentation, achieving state-of-the-art IoU 66.9% on CamVid with only 9.4M parameters.

Simon Jégou, Michal Drozdzal, David Vazquez et al.

Introduced GuessWhat?!, a multi-modal dialogue dataset with 150K games, advancing visual question answering and goal-oriented dialogue research.

Harm de Vries, Florian Strub, Sarath Chandar et al.

MV3D network fuses LIDAR and RGB data, achieving a 30% improvement in 3D detection accuracy on the KITTI dataset.

Xiaozhi Chen, Huimin Ma, Ji Wan et al.

iCaRL combines nearest-mean-of-exemplars classification with rehearsal and distillation, enabling long-term incremental learning and mitigating catastrophic forgetting.

Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl et al.

Proposes Deep Feature Flow, running expensive CNNs only on sparse key frames and propagating features via optical flow, achieving 10x speedup.

Xizhou Zhu, Yuwen Xiong, Jifeng Dai et al.

Proposes conditional GAN with U-Net and PatchGAN for image translation, achieving state-of-the-art results with high detail fidelity.

Phillip Isola, Jun-Yan Zhu, Tinghui Zhou et al.

Proposed TGAN with dual generators and Singular Value Clipping for stable, high-quality unsupervised video synthesis.

Masaki Saito, Eiichi Matsumoto, Shunta Saito

Integrating deep CNNs (YOLOv4) with GMM background modeling and multisensor fusion achieves 85% detection accuracy and 92% tracking continuity in maritime videos.

D. K. Prasad, D. Rajan, L. Rachmawati et al.

DSAC improves camera localization accuracy by 7.3% through differentiable RANSAC.

Eric Brachmann, Alexander Krull, Sebastian Nowozin et al.

ResNeXt introduces the 'cardinality' dimension, outperforming ResNet by increasing transformation paths, achieving higher accuracy with similar complexity.

Saining Xie, Ross Girshick, Piotr Dollár et al.

UNREAL combines A3C with multi-task auxiliary learning, boosting Atari and Labyrinth scores to 87%, with 10× faster learning.

Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki et al.

Constructed the COMICS dataset with 1.2 million panels; proposed three closure tasks; deep models lag behind humans, highlighting challenges in multimodal narrative understanding.

Mohit Iyyer, Varun Manjunatha, Anupam Guha et al.

Learned dexterous manipulation policies using trajectory optimization and deep learning; nearest neighbors achieved highest performance.

Vikash Kumar, Abhishek Gupta, Emanuel Todorov et al.

The paper learns SDP-rounding and agglomerative-clustering configurations, proving pseudodimension bounds from Θ(log n) to Θ(n).

Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik et al.

SummaRuNNer uses a bidirectional GRU sequence classifier with multi-feature integration, achieving state-of-the-art extractive summarization performance.

Ramesh Nallapati, Feifei Zhai, Bowen Zhou

Voxblox system incrementally converts TSDF to ESDF for real-time UAV path planning, achieving 20x faster updates with <0.1m error.

Helen Oleynikova, Zachary Taylor, Marius Fehr et al.